Images and videos are being disseminated in the open source, particularly on the internet, at an unprecedented rate. It is estimated that on average, every minute, hundreds of thousands of images are shared on social media websites alone. On YouTube, on average, over 100 hours of video comprising over 8 million images are shared every minute. This vast number of images can contain information that is highly valuable. For example, the ability to perform face recognition across the internet could be useful in finding exploited children, protecting or exploiting clandestine assets, locating war criminals, understanding criminal and terrorist networks, and other uses including but not limited to uses by the intelligence community, for cross-agency support, and in entertainment applications. Current known methods for searching images include text-based searching of “tags” that have been manually associated with particular images by humans, or searching for images that are a duplicate of an input image. Accordingly, there is a need for systems, methods, and interfaces that perform visual analytics, particularly automated face recognition, on a scale capable of processing the vast amount of image data available in the open source.